How to Apply
All applicants should submit a cover letter, a vita, three representative publications, evidence of teaching excellence, a statement of teaching philosophy and experience, a statement of current and future research plans, contributions to diversity, and three letters of recommendation. All application materials must be submitted electronically to: https://apply.interfolio.com/55148 . Please, direct enquiries about this position to, Dr. Margaret Hedstrom (email@example.com ). This is a rolling search and we plan to make offers as qualified candidates are identified. Consideration of applications will begin immediately.
The School of Information at the University of Michigan (UMSI) seeks tenure-track professors at the assistant, associate or full level in the multidisciplinary areas of digital curation, archival science, scientific data use and reuse. UMSI seeks applicants who can contribute to the research, teaching, and service missions of the school and the university. We anticipate a multi-year search with the possibility of multiple offers. Broadly construed, the research areas of interest include: digital curation technologies and methods; discovery, representation and interpretation of archival content and collections; open science and scholarship; provenance of data, objects, images, archival records, and collections; integrity and user acceptance of digital archives; metadata and information organization; and the economics of long-term sustainability. Examples of particular areas of focus include, but are not limited to:
- Sustainable access, dissemination, and preservation of digital data and archives.
- The development, application and evolution of data and metadata standards over time, and by different user communities.
- Ontologies and other semantic approaches (general and domain-specific) that make it possible to conceptualize, act, and reason about data.
- Provenance determination in digital data or born-digital records, and correspondingly, methods to automatically infer provenance.
- Policy, algorithmic, organizational, and practice-based methods to mitigate privacy problems with digital data.
- Digital forensics (media diagnostics, data recovery, analysis) for post-hoc extraction of data or metadata.
- Metrics and methods to determine the quality of data that originate from formal, such as research data, and informal sources, such as social media, crowdsourcing, citizen science, and sensors or other forms of passive data collection.Trust and quality in digital data and repositories.
- Interdisciplinary data reuse and integration of diverse data.
Each contributing member of the UMSI faculty is expected to have teaching effort equivalent to three residential courses per year. In addition to formal classroom and/or online teaching, faculty are expected to work with students by serving as advisors for independent studies, master’s projects and theses, and doctoral dissertations. Job duties include teaching, research and service. Additional job responsibilities include but are not limited to:
- Conducting scholarly research resulting in publications in peer reviewed journals, book chapters, edited books, books, and conference papers
- Seeking outside funding to support their research
- Providing service to the school, University, and the broader academic community by way of committee work, journal editing, and other various opportunities
- Ph.D. in an area such as information, computer science, social sciences, or other relevant area
- A strong interest in teaching at the undergraduate and graduate levels
- A proven record in teaching and research is desirable
- A strong commitment to teaching, interdisciplinary research, and cultural diversity
This position is posted as Assistant Professor/Associate Professor/Professor. The rank of the selected candidate will depend upon candidate qualifications.
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.